Business Intelligence applications in an enterprise

Business Intelligence can be applied to the following business purposes, in order to drive business value:

  1. Measurement – program that creates a hierarchy of performance metrics and benchmarking that informs business leaders about progress towards business goals.
  2. Analytics – program that builds quantitative processes for a business to arrive at optimal decisions and to perform business knowledge discovery. Frequently involves: data mining, process mining, statistical analysis, predictive analytics, predictive modeling, business process modeling, complex event processing and prescriptive analytics.
  3. Reporting / Enterprise reporting – program that builds infrastructure for strategic reporting to serve the strategic management of a business, not operational reporting. Frequently involves data visualization, executive information system and OLAP.
  4. Collaboration / Collaboration platform – program that gets different areas (both inside and outside the business) to work together through data sharing and electronic data interchange.
  5. Knowledge Management – program to make the company data driven through strategies and practices to identify, create, represent, distribute, and enable adoption of insights and experiences that are true business knowledge. Knowledge management leads to learning management and regulatory compliance.

In addition to above, business intelligence also can provide a pro-active approach, such as ALARM function to alert immediately to end-user. There are many types of alerts, for example if some business value exceeds the threshold value the color of that amount in the report will turn RED and the business analyst is alerted. Sometimes an alert mail will be sent to the user as well. This end to end process requires data governance, which should be handled by the expert.

Prioritization of business intelligence projects

It is often difficult to provide a positive business case for business intelligence initiatives and often the projects must be prioritized through strategic initiatives. Here are some hints to increase the benefits for a BI project.

  • As described by Kimball you must determine the tangible benefits such as eliminated cost of producing legacy reports.
  • Enforce access to data for the entire organization. In this way even a small benefit, such as a few minutes saved, makes a difference when multiplied by the number of employees in the entire organization.
  • As described by Ross, Weil & Roberson for Enterprise Architecture, consider letting the BI project be driven by other business initiatives with excellent business cases. To support this approach, the organization must have enterprise architects who can identify suitable business projects.
  • Use a structured and quantitative methodology to create defensible prioritization in line with the actual needs of the organization, such as a weighted decision matrix.

Success factors of BI implementation

Before implementing a BI solution, it is worth taking different factors into consideration before proceeding. According to Kimball et al., these are the three critical areas that you need to assess within your organization before getting ready to do a BI project:

  1. The level of commitment and sponsorship of the project from senior management
  2. The level of business need for creating a BI implementation
  3. The amount and quality of business data available

Business sponsorship

The commitment and sponsorship of senior management is according to Kimball et al., the most important criteria for assessment. This is because having strong management backing helps overcome shortcomings elsewhere in the project. However, as Kimball et al. state: “even the most elegantly designed DW/BI system cannot overcome a lack of business [management] sponsorship”.

It is important that management personnel who participate in the project have a vision and an idea of the benefits and drawbacks of implementing a BI system. The best business sponsor should have organizational clout and should be well connected within the organization. It is ideal that the business sponsor is demanding but also able to be realistic and supportive if the implementation runs into delays or drawbacks.

The management sponsor also needs to be able to assume accountability and to take responsibility for failures and setbacks on the project. Support from multiple members of the management ensures the project does not fail if one person leaves the steering group. However, having many managers work together on the project can also mean that there are several different interests that attempt to pull the project in different directions, such as if different departments want to put more emphasis on their usage.

This issue can be countered by an early and specific analysis of the business areas that benefit the most from the implementation. All stakeholders in project should participate in this analysis in order for them to feel ownership of the project and to find common ground.

Another management problem that should be encountered before start of implementation is if the business sponsor is overly aggressive. If the management individual gets carried away by the possibilities of using BI and starts wanting the DW or BI implementation to include several different sets of data that were not included in the original planning phase. However, since extra implementations of extra data may add many months to the original plan, it’s wise to make sure the person from management is aware of his actions.

Business needs

Because of the close relationship with senior management, another critical thing that must be assessed before the project begins is whether or not there is a business need and whether there is a clear business benefit by doing the implementation. The needs and benefits of the implementation are sometimes driven by competition and the need to gain an advantage in the market. Another reason for a business-driven approach to implementation of BI is the acquisition of other organizations that enlarge the original organization it can sometimes be beneficial to implement DW or BI in order to create more oversight.

Companies that implement BI are often large, multinational organizations with diverse subsidiaries. A well-designed BI solution provides a consolidated view of key business data not available anywhere else in the organization, giving management visibility and control over measures that otherwise would not exist.

Amount and quality of available data

Without good data, it does not matter how good the management sponsorship or business-driven motivation is. Without proper data, or with too little quality data, any BI implementation fails. Before implementation it is a good idea to do data profiling. This analysis identifies the “content, consistency and structure [..]” of the data. This should be done as early as possible in the process and if the analysis shows that data is lacking, put the project on the shelf temporarily while the IT department figures out how to properly collect data.

When planning for business data and business intelligence requirements, it is always advisable to consider specific scenarios that apply to a particular organization, and then select the business intelligence features best suited for the scenario.

Often, scenarios revolve around distinct business processes, each built on one or more data sources. These sources are used by features that present that data as information to knowledge workers, who subsequently act on that information. The business needs of the organization for each business process adopted correspond to the essential steps of business intelligence. These essential steps of business intelligence includes but not limited to:

  1. Go through business data sources in order to collect needed data
  2. Convert business data to information and present appropriately
  3. Query and analyze data
  4. Act on those data collected

From WikiPedia

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